Cover Image

Generative Modeling and Data Augmentation for Power System Production Simulation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Linna, Zhu, Yongli
Format:	Preprint
Published:	2024
Subjects:	Systems and Control Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On-Meter Graph Machine Learning: A Case Study of PV Power Forecasting for Grid Edge Intelligence
by: Huang, Jian, et al.
Published: (2026)

Diffusion-assisted Model Predictive Control Optimization for Power System Real-Time Operation
by: Xu, Linna, et al.
Published: (2025)

Embedded Machine Learning for Solar PV Power Regulation in a Remote Microgrid
by: Zhu, Yongli, et al.
Published: (2024)

ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement Learning
by: Wang, Maonan, et al.
Published: (2022)

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow with Continual Learning
by: Ezeakunne, Chidozie, et al.
Published: (2026)

gridfm-datakit-v1: A Python Library for Scalable and Realistic Power Flow and Optimal Power Flow Data Generation
by: Puech, Alban, et al.
Published: (2025)

RATE: An LLM-Powered Retrieval Augmented Generation Technology-Extraction Pipeline
by: Mirhosseini, Karan, et al.
Published: (2025)

Deep Reinforcement Learning for Power Grid Multi-Stage Cascading Failure Mitigation
by: Meng, Bo, et al.
Published: (2025)

Agentic Application in Power Grid Static Analysis: Automatic Code Generation and Error Correction
by: Wang, Qinjuan, et al.
Published: (2026)

Data-Driven Ground-Fault Location Method in Distribution Power System With Distributed Generation
by: Caporuscio, Mauro, et al.
Published: (2024)

On the Generalization of Data-Assisted Control in port-Hamiltonian Systems (DAC-pH)
by: Eslami, Mostafa, et al.
Published: (2025)

Large Language Model Powered Automated Modeling and Optimization of Active Distribution Network Dispatch Problems
by: Yang, Xu, et al.
Published: (2025)

Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation
by: Internò, Christian, et al.
Published: (2025)

Combining Physics-based and Data-driven Modeling for Building Energy Systems
by: Von Krannichfeldt, Leandro, et al.
Published: (2024)

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids
by: Balada, Christoph, et al.
Published: (2022)

MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generation
by: Abbineni, Pravallika, et al.
Published: (2025)

Data-driven Modeling of Combined Sewer Systems for Urban Sustainability: An Empirical Evaluation
by: Singh, Vipin, et al.
Published: (2024)

PowerGrow: Feasible Co-Growth of Structures and Dynamics for Power Grid Synthesis
by: He, Xinyu, et al.
Published: (2025)

SEAL: SEmantic-Augmented Imitation Learning via Language Model
by: Gu, Chengyang, et al.
Published: (2024)

Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutions
by: Za'ter, Muhy Eddin, et al.
Published: (2025)

Data Center Cooling System Optimization Using Offline Reinforcement Learning
by: Zhan, Xianyuan, et al.
Published: (2025)

Optimal Power Grid Operations with Foundation Models
by: Puech, Alban, et al.
Published: (2024)

Learning When to See for Long-term Traffic Data Collection on Power-constrained Devices
by: Zhang, Ruixuan, et al.
Published: (2024)

A General Approach of Automated Environment Design for Learning the Optimal Power Flow
by: Wolgast, Thomas, et al.
Published: (2025)

Synergies between Federated Foundation Models and Smart Power Grids
by: Hosseinalipour, Seyyedali, et al.
Published: (2025)

Multivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)

The Economic Dispatch of Power-to-Gas Systems with Deep Reinforcement Learning:Tackling the Challenge of Delayed Rewards with Long-Term Energy Storage
by: Sage, Manuel, et al.
Published: (2025)

A Personalized Data-Driven Generative Model of Human Repetitive Motion
by: Di Porzio, Angelo, et al.
Published: (2025)

PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks
by: Lin, Nan, et al.
Published: (2023)

Physically Plausible Multi-System Trajectory Generation and Symmetry Discovery
by: Liu, Jiayin, et al.
Published: (2025)

Operational Wind Speed Forecasts for Chile's Electric Power Sector Using a Hybrid ML Model
by: Suri, Dhruv, et al.
Published: (2024)

Newton's Lantern: A Reinforcement Learning Framework for Finetuning AC Power Flow Warm Start Models
by: Bose, Shourya, et al.
Published: (2026)

Generative AI and Process Systems Engineering: The Next Frontier
by: Decardi-Nelson, Benjamin, et al.
Published: (2024)

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework
by: Lin, Yu-Zheng, et al.
Published: (2024)

Data-driven Power Loss Identification through Physics-Based Thermal Model Backpropagation
by: Scarpa, Mattia, et al.
Published: (2025)

DCoPilot: Generative AI-Empowered Policy Adaptation for Dynamic Data Center Operations
by: Li, Minghao, et al.
Published: (2026)

Analyzing Generalization in Policy Networks: A Case Study with the Double-Integrator System
by: Zhang, Ruining, et al.
Published: (2023)

Transmission Interface Power Flow Adjustment: A Deep Reinforcement Learning Approach based on Multi-task Attribution Map
by: Liu, Shunyu, et al.
Published: (2024)

Detection Augmented Bandit Procedures for Piecewise Stationary MABs: A Modular Approach
by: Huang, Yu-Han, et al.
Published: (2025)

Multi-Objective Reinforcement Learning for Power Grid Topology Control
by: Lautenbacher, Thomas, et al.
Published: (2025)